From the course: Strategic Data Collection, Modeling, and Quality Management for AI Systems
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Getting clear on objectives
From the course: Strategic Data Collection, Modeling, and Quality Management for AI Systems
Getting clear on objectives
- [Instructor] If we've identified root causes of the issue we want to solve with an AI system, we need a framework to turn those insights into actionable objectives. This is where SMART goals come in. SMART is a powerful goal-setting methodology that ensures our objectives are clear, trackable and achievable. Without SMART goals, we risk creating vague objectives that are hard to measure or implement. SMART is an acronym that stands for specific, measurable, achievable, relevant and time-bound. When applied to data collection and AI projects, this framework helps ensure we're not just gathering data for data's sake, but working toward clear, actionable outcomes. Let's break down each component using an example of a retailer preparing for the holiday season and trying to predict which products customers will want, when they'll want them and how many they'll need. Let's look at each component of the SMART framework in this context. Specific. Instead of improve holiday forecasting, we…
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